The patient journeys of children and adolescents with depression: a study of electronic health records.

In England, children and adolescents with depression can seek treatment from specialist mental health services. We know little about how they journey through these services, or whether healthcare providers collect sufficient data to accurately appraise this. We aimed to summarise the child and adolescent depression pathway for two healthcare providers. This cohort study used de-identified electronic health records extracted from Cambridgeshire and Peterborough NHS Foundation Trust (CPFT) and South London and Maudsley NHS Foundation Trust (SLaM). We identified referrals between 2015 and 2019 during which the referred patient received their first depression diagnosis aged < 18 years. We described patient demographic and clinical characteristics, and features of the referral. In total, n = 296 (CPFT) and n = 2502 (SLaM) patients had a referral which met eligibility criteria. In both sites, patients were more frequently female (CPFT 79.3%; SLaM 69.3%) and White ethnicity (CPFT 88.9%; SLaM 57.9%) as compared to respective population estimates for the Trusts' catchment areas. Patients typically received their first depression diagnosis during adolescence (median ages 16 in CPFT and 15 in SLaM). The most common comorbidity was anxiety disorder. Referrals were usually routine, to community teams specialising in the child age group. Commonly mentioned interventions included antidepressant medication, cognitive behavioural therapy, and dialectical behaviour therapy. However, pathways varied within and between sites, and the quality and consistency of some data was poor. These findings provide an overview of service pathways experienced by children and adolescents with depression, but also highlight that pathways can vary according to individual need and healthcare provider. More systematic collection of some data, and standardisation in record systems used by different providers, would be beneficial.

Ethnicity, consanguinity, and genetic architecture of hypertrophic cardiomyopathy.

AIMS: Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity that is partly explained by the diversity of genetic variants contributing to disease. Accurate interpretation of these variants constitutes a major challenge for diagnosis and implementing precision medicine, especially in understudied populations. The aim is to define the genetic architecture of HCM in North African cohorts with high consanguinity using ancestry-matched cases and controls. METHODS AND RESULTS: Prospective Egyptian patients (n = 514) and controls (n = 400) underwent clinical phenotyping and genetic testing. Rare variants in 13 validated HCM genes were classified according to standard clinical guidelines and compared with a prospective HCM cohort of majority European ancestry (n = 684). A higher prevalence of homozygous variants was observed in Egyptian patients (4.1% vs. 0.1%, P = 2 × 10-7), with variants in the minor HCM genes MYL2, MYL3, and CSRP3 more likely to present in homozygosity than the major genes, suggesting these variants are less penetrant in heterozygosity. Biallelic variants in the recessive HCM gene TRIM63 were detected in 2.1% of patients (five-fold greater than European patients), highlighting the importance of recessive inheritance in consanguineous populations. Finally, rare variants in Egyptian HCM patients were less likely to be classified as (likely) pathogenic compared with Europeans (40.8% vs. 61.6%, P = 1.6 × 10-5) due to the underrepresentation of Middle Eastern populations in current reference resources. This proportion increased to 53.3% after incorporating methods that leverage new ancestry-matched controls presented here. CONCLUSION: Studying consanguineous populations reveals novel insights with relevance to genetic testing and our understanding of the genetic architecture of HCM.

COVID-related hospitalization, intensive care treatment, and all-cause mortality in patients with psychosis and treated with clozapine.

Clozapine, an antipsychotic, is associated with increased susceptibility to infection with COVID-19, compared to other antipsychotics. Here, we investigate associations between clozapine treatment and increased risk of adverse outcomes of COVID-19, namely COVID-related hospitalisation, intensive care treatment, and death, amongst patients taking antipsychotics with schizophrenia-spectrum disorders. Using the clinical records of South London and Maudsley NHS Foundation Trust, we identified 157 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders, were taking antipsychotics (clozapine or other antipsychotics) at the time of COVID-19 pandemic in the UK and had a laboratory-confirmed COVID-19 infection. The following health outcomes were measured: COVID-related hospitalisation, COVID-related intensive care treatment and death. We tested associations between clozapine treatment and each outcome using logistic regression models, adjusting for gender, age, ethnicity, neighbourhood deprivation, obesity, smoking status, diabetes, asthma, bronchitis and hypertension using propensity scores. Of the 157 individuals who developed COVID-19 while on antipsychotics (clozapine or other antipsychotics), there were 28% COVID-related hospitalisations, 8% COVID-related intensive care treatments and 8% deaths of any cause during the 28 days follow-up period. amongst those taking clozapine, there were 25% COVID-related hospitalisations, 7% COVID-related intensive care treatments and 7% deaths. In both unadjusted and adjusted analyses, we found no significant association between clozapine and any of the outcomes. Thus, we found no evidence that patients with clozapine treatment at time of COVID-19 infection had increased risk of hospitalisation, intensive care treatment or death, compared to non-clozapine antipsychotic-treated patients. However, further research should be considered in larger samples to confirm this.

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions.

PURPOSE: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene-disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. METHODS: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost's ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. RESULTS: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4-24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11-29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. CONCLUSIONS: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions ( https://www.cardiodb.org/cardioboost/ ), highlighting broad opportunities for improved pathogenicity prediction through disease specificity.

Clozapine treatment and risk of COVID-19 infection: retrospective cohort study.

BACKGROUND: Clozapine, an antipsychotic with unique efficacy in treatment-resistant psychosis, is associated with increased susceptibility to infection, including pneumonia. AIMS: To investigate associations between clozapine treatment and increased risk of COVID-19 infection in patients with schizophrenia-spectrum disorders who are receiving antipsychotic medications in a geographically defined population in London, UK. METHOD: Using information from South London and Maudsley NHS Foundation Trust (SLAM) clinical records, via the Clinical Record Interactive Search system, we identified 6309 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders and were taking antipsychotics at the time of the COVID-19 pandemic onset in the UK. People who were on clozapine treatment were compared with those on any other antipsychotic treatment for risk of contracting COVID-19 between 1 March and 18 May 2020. We tested associations between clozapine treatment and COVID-19 infection, adjusting for gender, age, ethnicity, body mass index (BMI), smoking status and SLAM service use. RESULTS: Of 6309 participants, 102 tested positive for COVID-19. Individuals who were on clozapine had increased risk of COVID-19 infection compared with those who were on other antipsychotic medication (unadjusted hazard ratio HR = 2.62, 95% CI 1.73-3.96), which was attenuated after adjusting for potential confounders, including clinical contact (adjusted HR = 1.76, 95% CI 1.14-2.72). CONCLUSIONS: These findings provide support for the hypothesis that clozapine treatment is associated with an increased risk of COVID-19 infection. Further research will be needed in other samples to confirm this association. Potential clinical implications are discussed.

The side effect profile of Clozapine in real world data of three large mental health hospitals.

OBJECTIVE: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing what we know from Randomised control trials (RCTs). We Propose a text mining approach to detect adverse events and medication episodes from the clinical text to enhance our understanding of adverse effects related to Clozapine, the most effective antipsychotic drug for the management of treatment-resistant schizophrenia, but underutilised due to concerns over its side effects. MATERIAL AND METHODS: We used data from de-identified EHRs of three mental health trusts in the UK (>50 million documents, over 500,000 patients, 2835 of which were prescribed Clozapine). We explored the prevalence of 33 adverse effects by age, gender, ethnicity, smoking status and admission type three months before and after the patients started Clozapine treatment. Where possible, we compared the prevalence of adverse effects with those reported in the Side Effects Resource (SIDER). RESULTS: Sedation, fatigue, agitation, dizziness, hypersalivation, weight gain, tachycardia, headache, constipation and confusion were amongst the highest recorded Clozapine adverse effect in the three months following the start of treatment. Higher percentages of all adverse effects were found in the first month of Clozapine therapy. Using a significance level of (p< 0.05) our chi-square tests show a significant association between most of the ADRs and smoking status and hospital admission, and some in gender, ethnicity and age groups in all trusts hospitals. Later we combined the data from the three trusts hospitals to estimate the average effect of ADRs in each monthly interval. In gender and ethnicity, the results show significant association in 7 out of 33 ADRs, smoking status shows significant association in 21 out of 33 ADRs and hospital admission shows the significant association in 30 out of 33 ADRs. CONCLUSION: A better understanding of how drugs work in the real world can complement clinical trials.

The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: defining a healthy volunteer cohort.

The integration of comprehensive genomic and phenotypic data from diverse ethnic populations offers unprecedented opportunities toward advancements in precision medicine and novel diagnostic technologies. Current reference genomic databases are not representative of the global human population, making variant interpretation challenging, especially in underrepresented populations, such as the North African population. To address this, the Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project launched a study comprising 1000 individuals free of cardiovascular disease (CVD). Here, we present the first 391 Egyptian healthy volunteers recruited to establish a pilot phenotyped control cohort. All individuals underwent detailed clinical investigation, including cardiac magnetic resonance imaging (MRI), and were sequenced using a targeted panel of 174 genes with reported roles in inherited cardiac conditions. We identified 1262 variants in 27 cardiomyopathy genes of which 15.1% were not captured in current global and regional genetic reference databases (here: gnomAD and Great Middle Eastern Variome). The ECCO-GEN project aims at defining the genetic landscape of an understudied population and providing individual-level genetic and phenotypic data to support future studies in CVD and population genetics.

Genetic Studies of Hypertrophic Cardiomyopathy in Singaporeans Identify Variants in TNNI3 and TNNT2 That Are Common in Chinese Patients.

BACKGROUND: To assess the genetic architecture of hypertrophic cardiomyopathy (HCM) in patients of predominantly Chinese ancestry. METHODS: We sequenced HCM disease genes in Singaporean patients (n=224) and Singaporean controls (n=3634), compared findings with additional populations and White HCM cohorts (n=6179), and performed in vitro functional studies. RESULTS: Singaporean HCM patients had significantly fewer confidently interpreted HCM disease variants (pathogenic/likely pathogenic: 18%, P<0.0001) but an excess of variants of uncertain significance (24%, P<0.0001), as compared to Whites (pathogenic/likely pathogenic: 31%, excess of variants of uncertain significance: 7%). Two missense variants in thin filament encoding genes were commonly seen in Singaporean HCM (TNNI3:p.R79C, disease allele frequency [AF]=0.018; TNNT2:p.R286H, disease AF=0.022) and are enriched in Singaporean HCM when compared with Asian controls (TNNI3:p.R79C, Singaporean controls AF=0.0055, P=0.0057, genome aggregation database-East Asian AF=0.0062, P=0.0086; TNNT2:p.R286H, Singaporean controls AF=0.0017, P<0.0001, genome aggregation database-East Asian AF=0.0009, P<0.0001). Both these variants have conflicting annotations in ClinVar and are of low penetrance (TNNI3:p.R79C, 0.7%; TNNT2:p.R286H, 2.7%) but are predicted to be deleterious by computational tools. In population controls, TNNI3:p.R79C carriers had significantly thicker left ventricular walls compared with noncarriers while its etiological fraction is limited (0.70 [95% CI, 0.35-0.86]) and thus TNNI3:p.R79C is considered variant of uncertain significance. Mutant TNNT2:p.R286H iPSC-CMs (induced pluripotent stem cells derived cardiomyocytes) show hypercontractility, increased metabolic requirements, and cellular hypertrophy and the etiological fraction (0.93 [95% CI, 0.83-0.97]) support the likely pathogenicity of TNNT2:p.R286H. CONCLUSIONS: As compared with Whites, Chinese HCM patients commonly have low penetrance risk alleles in TNNT2 or TNNI3 but exhibit few clinically actionable HCM variants overall. This highlights the need for greater study of HCM genetics in non-White populations.

Reevaluating the Genetic Contribution of Monogenic Dilated Cardiomyopathy.

BACKGROUND: Dilated cardiomyopathy (DCM) is genetically heterogeneous, with >100 purported disease genes tested in clinical laboratories. However, many genes were originally identified based on candidate-gene studies that did not adequately account for background population variation. Here we define the frequency of rare variation in 2538 patients with DCM across protein-coding regions of 56 commonly tested genes and compare this to both 912 confirmed healthy controls and a reference population of 60 706 individuals to identify clinically interpretable genes robustly associated with dominant monogenic DCM. METHODS: We used the TruSight Cardio sequencing panel to evaluate the burden of rare variants in 56 putative DCM genes in 1040 patients with DCM and 912 healthy volunteers processed with identical sequencing and bioinformatics pipelines. We further aggregated data from 1498 patients with DCM sequenced in diagnostic laboratories and the Exome Aggregation Consortium database for replication and meta-analysis. RESULTS: Truncating variants in TTN and DSP were associated with DCM in all comparisons. Variants in MYH7, LMNA, BAG3, TNNT2, TNNC1, PLN, ACTC1, NEXN, TPM1, and VCL were significantly enriched in specific patient subsets, with the last 2 genes potentially contributing primarily to early-onset forms of DCM. Overall, rare variants in these 12 genes potentially explained 17% of cases in the outpatient clinic cohort representing a broad range of adult patients with DCM and 26% of cases in the diagnostic referral cohort enriched in familial and early-onset DCM. Although the absence of a significant excess in other genes cannot preclude a limited role in disease, such genes have limited diagnostic value because novel variants will be uninterpretable and their diagnostic yield is minimal. CONCLUSIONS: In the largest sequenced DCM cohort yet described, we observe robust disease association with 12 genes, highlighting their importance in DCM and translating into high interpretability in diagnostic testing. The other genes analyzed here will need to be rigorously evaluated in ongoing curation efforts to determine their validity as Mendelian DCM genes but have limited value in diagnostic testing in DCM at present. This data will contribute to community gene curation efforts and will reduce erroneous and inconclusive findings in diagnostic testing.

The yield of postmortem genetic testing in sudden death cases with structural findings at autopsy.

Sudden cardiac death (SCD) is often associated with structural abnormalities of the heart during autopsy. This study sought to compare the diagnostic yield of postmortem genetic testing in (1) cases with structural findings of uncertain significance at autopsy to (2) cases with autopsy findings diagnostic of cardiomyopathy. We evaluated 57 SCD cases with structural findings at cardiac autopsy. Next-generation sequencing using a panel of 77 primary electrical disorder and cardiomyopathy genes was performed. Pathogenic and likely pathogenic variants were classified using American College of Medical Genetics (ACMG) consensus guidelines. In 29 cases (51%) autopsy findings of uncertain significance were identified whereas in 28 cases (49%) a diagnosis of cardiomyopathy was established. We identified a pathogenic or likely pathogenic variant in 10 cases (18%); in 1 (3%) case with non-specific autopsy findings compared with 9 (32%) cases with autopsy findings diagnostic of cardiomyopathy (p = 0.0054). The yield of genetic testing in SCD cases with autopsy findings consistent with cardiomyopathy is comparable with the yield in cardiomyopathy patients that are alive. Genetic testing in cases with findings of uncertain significance offers lower clinical utility than in cardiomyopathy, with lower yields than detected previously. This highlights the need for stringent evaluation of variant pathogenicity.

Genetic Variants Associated With Cancer Therapy-Induced Cardiomyopathy.

BACKGROUND: Cancer therapy-induced cardiomyopathy (CCM) is associated with cumulative drug exposures and preexisting cardiovascular disorders. These parameters incompletely account for substantial interindividual susceptibility to CCM. We hypothesized that rare variants in cardiomyopathy genes contribute to CCM. METHODS: We studied 213 patients with CCM from 3 cohorts: retrospectively recruited adults with diverse cancers (n=99), prospectively phenotyped adults with breast cancer (n=73), and prospectively phenotyped children with acute myeloid leukemia (n=41). Cardiomyopathy genes, including 9 prespecified genes, were sequenced. The prevalence of rare variants was compared between CCM cohorts and The Cancer Genome Atlas participants (n=2053), healthy volunteers (n=445), and an ancestry-matched reference population. Clinical characteristics and outcomes were assessed and stratified by genotypes. A prevalent CCM genotype was modeled in anthracycline-treated mice. RESULTS: CCM was diagnosed 0.4 to 9 years after chemotherapy; 90% of these patients received anthracyclines. Adult patients with CCM had cardiovascular risk factors similar to the US population. Among 9 prioritized genes, patients with CCM had more rare protein-altering variants than comparative cohorts ( P≤1.98e-04). Titin-truncating variants (TTNtvs) predominated, occurring in 7.5% of patients with CCM versus 1.1% of The Cancer Genome Atlas participants ( P=7.36e-08), 0.7% of healthy volunteers ( P=3.42e-06), and 0.6% of the reference population ( P=5.87e-14). Adult patients who had CCM with TTNtvs experienced more heart failure and atrial fibrillation ( P=0.003) and impaired myocardial recovery ( P=0.03) than those without. Consistent with human data, anthracycline-treated TTNtv mice and isolated TTNtv cardiomyocytes showed sustained contractile dysfunction unlike wild-type ( P=0.0004 and P<0.002, respectively). CONCLUSIONS: Unrecognized rare variants in cardiomyopathy-associated genes, particularly TTNtvs, increased the risk for CCM in children and adults, and adverse cardiac events in adults. Genotype, along with cumulative chemotherapy dosage and traditional cardiovascular risk factors, improves the identification of patients who have cancer at highest risk for CCM. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifiers: NCT01173341; AAML1031; NCT01371981.

Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy.

BACKGROUND: International guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework. METHODS: We compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts (up to 6179 cases) to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases. RESULTS: Analysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. Applying this approach leads to an estimated 14-20% increase in cases with actionable HCM variants, i.e. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands' relatives. CONCLUSIONS: When found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a "likely pathogenic" classification, even without additional segregation or functional data. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consistent and unbiased approach to variant interpretation for Mendelian disease genetic testing. We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner.

Genetic Etiology for Alcohol-Induced Cardiac Toxicity.

BACKGROUND: Alcoholic cardiomyopathy (ACM) is defined by a dilated and impaired left ventricle due to chronic excess alcohol consumption. It is largely unknown which factors determine cardiac toxicity on exposure to alcohol. OBJECTIVES: This study sought to evaluate the role of variation in cardiomyopathy-associated genes in the pathophysiology of ACM, and to examine the effects of alcohol intake and genotype on dilated cardiomyopathy (DCM) severity. METHODS: The authors characterized 141 ACM cases, 716 DCM cases, and 445 healthy volunteers. The authors compared the prevalence of rare, protein-altering variants in 9 genes associated with inherited DCM. They evaluated the effect of genotype and alcohol consumption on phenotype in DCM. RESULTS: Variants in well-characterized DCM-causing genes were more prevalent in patients with ACM than control subjects (13.5% vs. 2.9%; p = 1.2 ×10-5), but similar between patients with ACM and DCM (19.4%; p = 0.12) and with a predominant burden of titin truncating variants (TTNtv) (9.9%). Separately, we identified an interaction between TTN genotype and excess alcohol consumption in a cohort of DCM patients not meeting ACM criteria. On multivariate analysis, DCM patients with a TTNtv who consumed excess alcohol had an 8.7% absolute reduction in ejection fraction (95% confidence interval: -2.3% to -15.1%; p < 0.007) compared with those without TTNtv and excess alcohol consumption. The presence of TTNtv did not predict phenotype, outcome, or functional recovery on treatment in ACM patients. CONCLUSIONS: TTNtv represent a prevalent genetic predisposition for ACM, and are also associated with a worse left ventricular ejection fraction in DCM patients who consume alcohol above recommended levels. Familial evaluation and genetic testing should be considered in patients presenting with ACM.

CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation.

PURPOSE: Internationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier ( http://www.cardioclassifier.org ), a semiautomated decision-support tool for inherited cardiac conditions (ICCs). METHODS: CardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules. RESULTS: We benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher's P = 1.1 × 10-18), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data. CONCLUSION: CardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.

Phenotype and Clinical Outcomes of Titin Cardiomyopathy.

BACKGROUND: Improved understanding of dilated cardiomyopathy (DCM) due to titin truncation (TTNtv) may help guide patient stratification. OBJECTIVES: The purpose of this study was to establish relationships among TTNtv genotype, cardiac phenotype, and outcomes in DCM. METHODS: In this prospective, observational cohort study, DCM patients underwent clinical evaluation, late gadolinium enhancement cardiovascular magnetic resonance, TTN sequencing, and adjudicated follow-up blinded to genotype for the primary composite endpoint of cardiovascular death, and major arrhythmic and major heart failure events. RESULTS: Of 716 subjects recruited (mean age 53.5 ± 14.3 years; 469 men [65.5%]; 577 [80.6%] New York Heart Association function class I/II), 83 (11.6%) had TTNtv. Patients with TTNtv were younger at enrollment (49.0 years vs. 54.1 years; p = 0.002) and had lower indexed left ventricular mass (5.1 g/m2 reduction; padjusted = 0.03) compared with patients without TTNtv. There was no difference in biventricular ejection fraction between TTNtv+/- groups. Overall, 78 of 604 patients (12.9%) met the primary endpoint (median follow-up 3.9 years; interquartile range: 2.0 to 5.8 years), including 9 of 71 patients with TTNtv (12.7%) and 69 of 533 (12.9%) without. There was no difference in the composite primary outcome of cardiovascular death, heart failure, or arrhythmic events, for patients with or without TTNtv (hazard ratio adjusted for primary endpoint: 0.92 [95% confidence interval: 0.45 to 1.87]; p = 0.82). CONCLUSIONS: In this large, prospective, genotype-phenotype study of ambulatory DCM patients, we show that prognostic factors for all-cause DCM also predict outcome in TTNtv DCM, and that TTNtv DCM does not appear to be associated with worse medium-term prognosis.

Utility of Post-Mortem Genetic Testing in Cases of Sudden Arrhythmic Death Syndrome.

BACKGROUND: Sudden arrhythmic death syndrome (SADS) describes a sudden death with negative autopsy and toxicological analysis. Cardiac genetic disease is a likely etiology. OBJECTIVES: This study investigated the clinical utility and combined yield of post-mortem genetic testing (molecular autopsy) in cases of SADS and comprehensive clinical evaluation of surviving relatives. METHODS: We evaluated 302 expertly validated SADS cases with suitable DNA (median age: 24 years; 65% males) who underwent next-generation sequencing using an extended panel of 77 primary electrical disorder and cardiomyopathy genes. Pathogenic and likely pathogenic variants were classified using American College of Medical Genetics (ACMG) consensus guidelines. The yield of combined molecular autopsy and clinical evaluation in 82 surviving families was evaluated. A gene-level rare variant association analysis was conducted in SADS cases versus controls. RESULTS: A clinically actionable pathogenic or likely pathogenic variant was identified in 40 of 302 cases (13%). The main etiologies established were catecholaminergic polymorphic ventricular tachycardia and long QT syndrome (17 [6%] and 11 [4%], respectively). Gene-based rare variants association analysis showed enrichment of rare predicted deleterious variants in RYR2 (p = 5 × 10-5). Combining molecular autopsy with clinical evaluation in surviving families increased diagnostic yield from 26% to 39%. CONCLUSIONS: Molecular autopsy for electrical disorder and cardiomyopathy genes, using ACMG guidelines for variant classification, identified a modest but realistic yield in SADS. Our data highlighted the predominant role of catecholaminergic polymorphic ventricular tachycardia and long QT syndrome, especially the RYR2 gene, as well as the minimal yield from other genes. Furthermore, we showed the enhanced utility of combined clinical and genetic evaluation.